T. Jagadesh^1,2, B. Sheela Rani^3,*

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 449-463, 2023, DOI:10.32604/iasc.2023.026868 - 06 June 2022

Abstract Interference is a key factor in radar return misdetection. Strong interference might make it difficult to detect the signal or targets. When interference occurs in the sidelobes of the antenna pattern, Sidelobe Cancellation (SLC) and Sidelobe Blanking are two unique solutions to solve this problem (SLB). Aside from this approach, the probability of false alert and likelihood of detection are the most essential parameters in radar. The chance of a false alarm for any radar system should be minimal, and as a result, the probability of detection should be high. There are several interference cancellation… More >

Salman A. Albinali¹, David R. Jacques²

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 1-17, 2014, DOI:10.3970/sdhm.2014.010.001

Abstract An analytic approach to exploring the tradespace associated with Structural Health Monitoring (SHM) systems is presented. Modeling and simulation of the life cycle of a legacy aircraft and the expected operational and maintenance events that could occur is shown. A focus on the SHM system detection of a significant crack length and the possibility of False Alarm (FA), miss detection and mishap events is investigated. The modeling approach allows researchers to explore the tradespace associated with safe and critical crack lengths, sensor thresholds, scheduled maintenance intervals, falsely triggered maintenance actions, and mishaps due to missed… More >

Jae Bong Lee¹, Jai Hak Park¹, Sung Ho Lee², Hong-Deok Kim², Han-Sub Chung²

CMES-Computer Modeling in Engineering & Sciences, Vol.11, No.1, pp. 9-16, 2006, DOI:10.3970/cmes.2006.011.009

Abstract The growth of stress corrosion cracks in steam generator tubes is predicted using the Monte Carlo simulation and statistical approaches. The statistical parameters that represent the characteristics of crack growth and crack initiation are derived from in-service inspection (ISI) non-destructive evaluation (NDE) data. Based on the statistical approaches, crack growth models are proposed and applied to predict crack distribution at the end of cycle (EOC). Because in-service inspection (ISI) crack data is different from physical crack data, a simple method for predicting the physical number of cracks from periodic in-service inspection data is proposed in More >